Srinivas Narayana will present his research seminar/general exam on Thursday Jan 19 at 10AM in Room 402. The members of his committee are: Jen Rexford (advisor), Mung Chiang, and Moses Charikar. Everyone is invited to attend his talk and those faculty wishing to remain for the oral exam following are welcome to do so. His abstract and reading list follow below. ---------------------------- Abstract: The end-to-end performance of user-facing online services (e.g., Facebook, Amazon) is critical to their operation, as small increases in user-perceived latencies can have significant impact on revenue. Such services typically run out of a number of geographically distributed data centers, each connected by multiple ISPs to the Internet, and a geographically distributed set of mapping nodes directing user requests to data centers (e.g., based on proximity). Together, request-mapping (i.e., assigning user requests to data centers) and response-routing decisions (i.e., choosing an ISP to send responses) determine the wide-area paths traversed by user traffic--which are a significant contributor to end-to-end service latency. Yet in today's systems, request-mapping and response-routing decisions are made almost independently with coarse-grained, if any, coordination--due to concerns of administrative separation and operational scale. In this work, we investigate the benefits of coordinating request-mapping and response-routing decisions, through an optimization framework. We identify how suboptimal performance or costs can result if (1) the mapping and routing systems have incompatible objectives, or (2) if they are not sharing their decisions, and even if (3) mapping and routing systems have compatible objectives, share decisions, and optimize on top of each other. To overcome these difficulties, we show how to perform jointly optimized mapping and routing decisions while retaining their administrative separation. In particular, we construct a provably optimal distributed algorithm implemented through local computations at mapping nodes and data center edge routers, with a lightweight exchange of decisions. Evaluations of our solution using traffic traces from an operational content distribution network shows that our system converges quickly in practice, and offers much better performance and lower costs than today's solutions. and reading list: (1) The Design Philosophy of the DARPA Internet Protocols D. D. Clark (2) End-to-end arguments in system design J.H. Saltzer, D.P. Reed and D.D. Clark (3) DONAR: Decentralized server selection for cloud services P. Wendell, J. W. Jiang, M. J. Freedman, and J. Rexford (4) Characterizing roles of front-end servers in end-to-end performance of dynamic content distribution Y. Chen, S. Jain, V. K. Adhikari, and Z. L. Zhang (5) Optimizing cost and performance for multi-homing D. K. Goldenberg, L. Qiu, H. Xie, Y. R. Yang, and Y. Zhang (6) Optimizing cost and performance in online service provider networks Z. Zhang, M. Zhang, A. Greenberg, Y. C. Hu, R. Mahajan, and B. Christian (7) Cooperative content distribution and traffic engineering in an ISP network J. W. Jiang, R. Zhang-Shen, J. Rexford and M. Chiang (8) Traffic engineering vs. Content distribution: A game theoretic perspective D. DiPalantino and R. Johari (9) A Tutorial on Decomposition Methods for Network Utility Maximization D. P. Palomar and M. Chiang (10) Democratizing content publication with Coral M. J. Freedman, E. Freudenthal and D. Mazieres (11) iPlane: An information plane for distributed services H. V. Madhyastha, T. Isdal, M. Piatek, C. Dixon, T. Anderson, A. Krishnamurthy and A. Venkataramani (12) Computer networks: a systems approach Larry L. Peterson and Bruce S. Davie